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High-Rate Four Photon Subtraction from Squeezed Vacuum: Preparing Cat State for Optical Quantum Computation

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arXiv 2025年

作者： Endo, Mamoru Nomura, Takefumi Sonoyama, Tatsuki Takahashi, Kazuma Takasu, Sachiko Fukuda, Daiji Kashiwazaki, Takahiro Inoue, Asuka Umeki, Takeshi Nehra, Rajveer Marek, Petr Filip, Radim Takase, Kan Asavanant, Warit Furusawa, Akira Department of Applied Physics School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo Tokyo113-8656 Japan Optical Quantum Computing Research Team RIKEN Center for Quantum Computing 2-1 Hirosawa Saitama Wako351-0198 Japan National Institute of Advanced Industrial Science and Technology 1-1-1 Umezono Ibaraki Tsukuba305-8563 Japan AIST-UTokyo Advanced Operando-Measurement Technology Open Innovation Laboratory 1-1-1 Umezono Ibaraki Tsukuba305-8563 Japan NTT Device Technology Labs NTT Corporation 3-1 Morinosato Wakamiya Kanagawa Atsugi243-0198 Japan Department of Electrical and Computer Engineering University of Massachusetts Amherst 100 Natural Resources Rd AmherstMA01003 United States Department of Physics University of Massachusetts Amherst 100 Natural Resources Rd AmherstMA01003 United States College of Information and Computer Science University of Massachusetts Amherst 100 Natural Resources Rd AmherstMA01003 United States Department of Optics Palacky University 17. listopadu 1192/12 Olomouc77146 Czech Republic

Generating logical qubits, essential for error detection and correction in quantum computation, remains a critical challenge in continuous-variable (CV) optical quantum information processing. The Gottesman-Kitaev-Preskill (GKP) code is a leading candidate for logical qubits, and its generation requires large-amplitude coherent state superpositions—Schrödinger cat states. However, experimentally producing these resource states has been hindered in the optical domain by technical challenges. The photon subtraction method, a standard approach for generating cat states using a squeezed vacuum and a photon number-resolving detector, has proven difficult to scale to multi-photon operations. While the amplitude of the generated cat states increases with the number of subtracted photons, limitations in the generation rate have restricted the maximum photon subtraction to n = 3 for over a decade. In this work, we demonstrate high-rate photon subtraction of up to four photons from a squeezed vacuum with picosecond wavepackets generated by a broadband optical parametric amplifier. Using a Ti-Au superconducting-transition-edge sensor, we achieve high-speed, high-resolution photon number discrimination. The resulting states exhibit Wigner function negativity without loss correction, and their quantum coherence is verified through off-diagonal density matrix elements in CV representation. These results overcome long-standing limitations in multi-photon operations, providing a critical foundation for generating quantum resources essential for fault-tolerant quantum computing and advancing ultrafast optical quantum processors. Copyright © 2025, The Authors. All rights reserved.

关键词： Parametric amplifiers

Detection Interval for Diffusion Molecular Communication: How Long is Enough?

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arXiv 2022年

作者： Chen, Xuan Wen, Miaowen Ji, Fei Huang, Yu Tang, Yuankun Eckford, Andrew W. The School of Electronics and Information Engineering South China University of Technology Guangzhou510641 China The Department of Electrical Engineering and Computer Science York University TorontoM3J 1P3 Canada The School of Electronic and Information Engineering South China University of Technology Guangzhou510640 China The School of Electronics and Communication Engineering Guangzhou University Guangzhou510006 China

Molecular communication has a key role to play in future medical applications, including detecting, analyzing, and addressing infectious disease outbreaks. Overcoming inter-symbol interference (ISI) is one of the key challenges in the design of molecular communication systems. In this paper, we propose to optimize the detection interval to minimize the impact of ISI while ensuring the accurate detection of the transmitted information symbol, which is suitable for the absorbing and passive receivers. For tractability, based on the signal-to-interference difference (SID) and signal-to-interference-and-noise amplitude ratio (SINAR), we propose a modified-SINAR (mSINAR) to measure the bit error rate (BER) performance for the molecular communication system with a variable detection interval. Besides, we derive the optimal detection interval in closed form. Using simulation results, we show that the BER performance of our proposed mSINAR scheme is superior to the competing schemes, and achieves similar performance to optimal intervals found by exhaustive search. Copyright © 2022, The Authors. All rights reserved.

关键词： Bit error rate

Low Complexity First: Duration-Centric ISI Mitigation in Molecular Communication via Diffusion

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arXiv 2022年

作者： Chen, Xuan Ji, Fei Wen, Miaowen Huang, Yu Tang, Yuankun Eckford, Andrew W. The School of Electronics and Information Engineering South China University of Technology Guangzhou510641 China The Department of Electrical Engineering and Computer Science York University TorontoM3J 1P3 Canada The School of Electronic and Information Engineering South China University of Technology Guangzhou510640 China The School of Electronics and Communication Engineering Guangzhou University Guangzhou510006 China

In this paper, we propose a novel inter-symbol interference (ISI) mitigation scheme for molecular communication via diffusion (MCvD) systems with optimal detection interval. Its rationale is to exploit the discarded duration (i.e., the symbol duration outside this optimal interval) to relieve ISI in the target system. Following this idea, we formulate an objective function to quantify the impact of the discarded time on bit error rate (BER) performance. Besides, an optimally reusable interval within the discarded duration is derived in closed form, which applies to both the absorbing and passive receivers. Finally, numerical results validate our analysis and show that for the considered MCvD system, significant BER improvements can be achieved by using the derived reusable duration. Copyright © 2022, The Authors. All rights reserved.

关键词： Bit error rate

Design of unwinnable persuasive game with level of difficulty structure

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AIP Conference Proceedings 2023年第1期2654卷

作者： Reza Giga Isnanda Paulus Insap Santosa Rudy Hartanto 1Department of Electrical and Information Engineering Faculty of Engineering Universitas Gadjah Mada Yogyakarta 55281 Indonesia 2Department of Information Technology Faculty of Engineering Universitas Muhammadiyah Yogyakarta Yogyakarta 55183 Indonesia

The effectiveness of unwinnable persuasive games to persuade players by utilizing game loss and the subsequent experience has not been established with empirical evidence. In addition, game loss can result in negative experiences which might hinder the persuasion process. Therefore, it is essential to validate its effectiveness and gain insight on how game loss can contribute to the persuasion process. To answer that, we decided to examine the role of frustration and playing duration in unwinnable persuasive games by employing value-added approach. With this approach, it is necessary to compare two or more similar games which differ only on the game properties whose effect is the focus of the research. Therefore, an existing game that can be manipulated easily will be advantageous in creating comparable experimental conditions. However, it might be difficult to find a game that meets all our requirements. Hence, we decided to develop our own game. This paper will elaborate on how we designed the game which enabled us to investigate the role of frustration and playing duration in unwinnable persuasive games. In addition, we explain how we created the level of difficulty structure to manipulate the independent variables to ensure that the produced games can be utilized to create comparable experimental conditions.

关键词：

Secure Beamforming Design for Rate-Splitting Multiple Access in Multi-antenna Broadcast Channel with Confidential Messages

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arXiv 2022年

作者： Xia, Huiyun Mao, Yijie Zhou, Xiaokang Clerckx, Bruno Han, Shuai Li, Cheng School of Electronics and Information Engineering Harbin Institute of Technology Harbin150001 China School of Information Science and Technology ShanghaiTech University Shanghai China Department of Electrical and Electronic Engineering Imperial College London London United Kingdom Electrical and Computer Engineering Faculty of Engineering and Applied Science Memorial University St. John’sA1B 3X5 Canada

As physical layer security evolves to multi-user systems, multi-user interference (MUI) becomes an unavoidable issue. Recently, rate-splitting multiple access (RSMA) emerges as a powerful non-orthogonal transmission framework and interference management strategy with high spectral efficiency. Unlike most works fully treating MUI as noise, we take all users’ secrecy rate requirements into consideration and propose an RSMA-based secure beamforming approach to maximize the weighted sum-rate (WSR), where MUI is partially decoded and partially treated as noise. User messages are split and encoded into common and private streams. Each user not only decodes the common stream and the intended private stream, but also tries to eavesdrop other users’ private streams. A successive convex approximation (SCA)-based approach is proposed to maximize the instantaneous WSR under perfect channel state information at the transmitter (CSIT). We then propose a joint weighted minimum mean square error and SCA-based alternating optimization algorithm to maximize the weighted ergodic sum-rate under imperfect CSIT. Numerical results demonstrate RSMA achieves better WSR and is more robust to channel errors than conventional multi-user linear precoding technique while ensuring all users’ security requirements. Besides, RSMA can satisfy all users’ secrecy rate requirements without introducing WSR loss thanks to its powerful interference management capability. Copyright © 2022, The Authors. All rights reserved.

关键词： Beamforming

MobVGG: Ensemble technique for birds and drones prediction

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Heliyon 2024年第21期10卷 e39537页

作者： Muhammad Saqib, Sheikh Mazhar, Tehseen Iqbal, Muhammad Almogren, Ahmad Shahazad, Tariq Rehman, Ateeq Ur Hamam, Habib Department of Computing and Information Technology Gomal University Dera Ismail Khan 29220 Pakistan Department of Computer Science School Education Department Government of Punjab Layyah 31200 Pakistan Chair of Cyber Security Department of Computer Science College of Computer and Information Sciences King Saud University Riyadh 11633 Saudi Arabia Department of Computer Science COMSATS University Islamabad Sahiwal Campus Sahiwal 57000 Pakistan School of Computing Gachon University Seongnam 13120 South Korea Faculty of Engineering Uni de Moncton Moncton E1A3E9 NB Canada School of Electrical Engineering University of Johannesburg Johannesburg 2006 South Africa International Institute of Technology and Management (IITG) Av. Grandes Ecoles Libreville BP 1989 Gabon Bridges for Academic Excellence - Spectrum Tunis Tunisia

Detection of aerial activities, including drones and birds, has practical implications for automating bird surveys and developing radar systems for aerial object collision detection. Convolutional neural networks (CNNs) have been extensively utilized for image recognition and classification tasks, albeit prior research predominantly focuses on single-class 'drone' classification. However, a gap persists in achieving high accuracy for multi-class classification. To address the limitations of traditional CNNs, such as vanishing gradients and the necessity for numerous layers, this study introduces a novel model termed "MobVGG.” This model combines the architectures of MobileNetV2 and VGG16 to accurately classify images as either 'bird' or 'drone'. The dataset comprises 4212 images for each category of 'bird' and 'drone'. The stringent methodology was applied for dataset preparation and model training to ensure the reliability of the findings. Comparative analysis with previous research demonstrates that the proposed MobVGG model, trained on both 'bird' and 'drone' images, achieves superior accuracy (96 %) compared to benchmark studies. Our paper targets researchers and graduate students as its primary audience. © 2024 The Authors

关键词： Convolutional neural networks (CNNs) Deep learning Ensemble technique MobileNetV2 VGG16

Neuromorphic spatiotemporal optical flow: Enabling ultrafast visual perception beyond human capabilities

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arXiv 2024年

作者： Wang, Shengbo Zhao, Jingwen Pu, Tongming Zhao, Liangbing Guo, Xiaoyu Cheng, Yue Li, Cong Ma, Weihao Tang, Chenyu Xu, Zhenyu Wang, Ningli Occhipinti, Luigi Nathan, Arokia Dahiya, Ravinder Wu, Huaqiang Tao, Li Gao, Shuo School of Instrumentation and Optoelectronic Engineering Beihang University Beijing100191 China School of Physics Center for Interdisciplinary Science of Optical Quantum and NEMS Integration Beijing Institute of Technology Beijing100081 China Computer Science Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Department of Mechanical Engineering City University of Hong Kong 83 Tat Chee Avenue Hong Kong Department of Engineering University of Cambridge CambridgeCB2 1PZ United Kingdom Department of Precision Instrument Tsinghua University Beijing100084 China Beijing Tongren Hospital Capital Medical University Beijing100005 China Darwin College University of Cambridge CambridgeCB2 1PZ United Kingdom School of Information Science and Engineering Shandong University Qingdao266237 China Group Department of Electrical and Computer Engineering Northeastern University BostonMA02115 United States School of Integrated Circuits Tsinghua University Beijing100084 China

Optical flow, inspired by the mechanisms of biological visual systems, calculates spatial motion vectors within visual scenes that are necessary for enabling robotics to excel in complex and dynamic working environments. However, current optical flow algorithms, despite human-competitive task performance on benchmark datasets, remain constrained by unacceptable time delays (~0.6 seconds per inference, 4X human processing speed) in practical deployment. Here, we introduce a neuromorphic optical flow approach that addresses delay bottlenecks by encoding temporal information directly in a synaptic transistor array to assist spatial motion analysis. Compared to conventional spatial-only optical flow methods, our spatiotemporal neuromorphic optical flow offers the spatial-temporal consistency of motion information, rapidly identifying regions of interest in as little as 1–2 ms using the temporal motion cues derived from the embedded temporal information in the two-dimensional floating gate synaptic transistors. Thus, the visual input can be selectively filtered to achieve faster velocity calculations and various task execution. At the hardware level, due to the atomically sharp interfaces between distinct functional layers in two-dimensional van der Waals heterostructures, the synaptic transistor offers high-frequency response (~100 μs), robust non-volatility (>104 s), and excellent endurance (>8,000 cycles), enabling robust visual processing. In software benchmarks, our system outperforms state-of-the-art algorithms with a 400% speedup, frequently surpassing human-level performance while maintaining or enhancing accuracy by utilizing the temporal priors provided by the embedded temporal information. © 2024, CC BY.

关键词： Van der Waals forces

Fusion Dilated CNN for Encrypted Web Traffic Classification

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International Journal of Network Security 2022年第4期24卷 733-740页

作者： Appiah, Benjamin Sackey, Anthony Kingsley Kwabena, Owusu-Agyemang Kanpogninge, Ansuura JohnBosco Aristotle Buah, Peter Antwi Department of Computer Science Ho Technical University1 Ho Volta Region Ghana School of Information and Software Engineering University of Electronic Science and Technology of China China C. K. Tedam University of Technology Applied Sciences Ghana Department of Civil Engineering Southwest Jiaotong University China

A Growing number of conventional Convolutional neural network (CNN) models have been employed for encrypted web traffic characterization. However, the application of CNN models is confronted with two significant challenges;a) they possess short reflective fields that don’t gather much-encrypted traffic information for effective and accurate predictions. b) these models are not adaptive to the diverse nature of traffic flow because of their singlehead architecture. This paper alleviates these problems using the fusion of dilated Convolutional neural networks dubbed FDCNN. FDCNN architecture supports exponentially large receptive fields and captures local dependencies in encrypted traffic data. The experimental results on public datasets, ISCX VPNnon-VPN Traffic datasets, indicate that FDCNN architecture is practical and achieves higher accuracy. © Institute of Mathematical Statistics, 2022

关键词： Convolution

Real-Time Metric-Semantic Mapping for Autonomous Navigation in Outdoor Environments

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arXiv 2024年

作者： Jiao, Jianhao Geng, Ruoyu Li, Yuanhang Xin, Ren Yang, Bowen Wu, Jin Wang, Lujia Liu, Ming Fan, Rui Kanoulas, Dimitrios Department of Computer Science University College London LondonWC1E 6BT United Kingdom Nansha Guangdong Guangzhou511400 China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong Nansha Guangdong Guangzhou511400 China College of Electronics and Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems The State Key Laboratory of Intelligent Autonomous Systems The Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai201804 China

The creation of a metric-semantic map, which encodes human-prior knowledge, represents a high-level abstraction of environments. However, constructing such a map poses challenges related to the fusion of multi-modal sensor data, the attainment of real-time mapping performance, and the preservation of structural and semantic information consistency. In this paper, we introduce an online metric-semantic mapping system that utilizes LiDAR-Visual-Inertial sensing to generate a global metric-semantic mesh map of large-scale outdoor environments. Leveraging GPU acceleration, our mapping process achieves exceptional speed, with frame processing taking less than 7ms, regardless of scenario scale. Furthermore, we seamlessly integrate the resultant map into a real-world navigation system, enabling metric-semantic-based terrain assessment and autonomous point-to-point navigation within a campus environment. Through extensive experiments conducted on both publicly available and self-collected datasets comprising 24 sequences, we demonstrate the effectiveness of our mapping and navigation methodologies. Code has been publicly released: https://***/gogojjh/cobra. Note to Practitioners—This paper tackles the challenge of autonomous navigation for mobile robots in complex, unstructured environments with rich semantic elements. Traditional navigation relies on geometric analysis and manual annotations, struggling to differentiate similar structures like roads and sidewalks. We propose an online mapping system that creates a global metric-semantic mesh map for large-scale outdoor environments, utilizing GPU acceleration for speed and overcoming the limitations of existing real-time semantic mapping methods, which are generally confined to indoor settings. Our map integrates into a real-world navigation system, proven effective in localization and terrain assessment through experiments with both public and proprietary datasets. Future work will focus on integrating kernel-based

关键词： Mesh generation